论文标题
使用ARX控制器模型的VRFT并限制了总正方形
VRFT with ARX controller model and constrained total least squares
论文作者
论文摘要
虚拟参考反馈调整（VRFT）是一种非题数据驱动（DD）方法，用于调整旨在实现规定的闭环性能的控制器参数。在最常见的公式中，通过求解最小二乘问题（LS）问题来估计线性参数化控制器的参数，在存在噪声的情况下，这会导致对控制器参数的偏差估计。为了消除这种偏见，该方法的仪器变量（IV）变体通常是以显着增加估计差异为代价的。在目前的工作中，我们建议将约束的最小二乘（CTL）解决方案应用于VRFT问题。我们用CTL明确制定了由自回归外源性（ARX）模型描述的控制器的CTL溶液。两种案例研究将其与通常的VRFT溶液以及另一种统计高效的设计方法进行了比较来说明拟议溶液的有效性。
The virtual reference feedback tuning (VRFT) is a non-iterative data-driven (DD) method employed to tune a controller's parameters aiming to achieve a prescribed closed-loop performance. In its most common formulation, the parameters of a linearly parametrized controller are estimated by solving a least squares (LS) problem, which in the presence of noise leads to a biased estimate of the controller's parameters. To eliminate this bias, an instrumental variable (IV) variant of the method is usual, at the cost of increasing significantly the estimate's variance. In the present work, we propose to apply the constrained total least squares (CTLS) solution to the VRFT problem. We formulate explicitly the VRFT solution with CTLS for controllers described by an autoregressive exogenous (ARX) model. The effectiveness of the proposed solution is illustrated by two case studies in which it is compared to the usual VRFT solutions and to another, statistically efficient, design method.
